Guibing Guo

4.2k total citations · 1 hit paper
91 papers, 2.5k citations indexed

About

Guibing Guo is a scholar working on Information Systems, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Guibing Guo has authored 91 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Information Systems, 61 papers in Artificial Intelligence and 27 papers in Management Science and Operations Research. Recurrent topics in Guibing Guo's work include Recommender Systems and Techniques (62 papers), Advanced Bandit Algorithms Research (26 papers) and Advanced Graph Neural Networks (20 papers). Guibing Guo is often cited by papers focused on Recommender Systems and Techniques (62 papers), Advanced Bandit Algorithms Research (26 papers) and Advanced Graph Neural Networks (20 papers). Guibing Guo collaborates with scholars based in China, Singapore and United Kingdom. Guibing Guo's co-authors include Jie Zhang, Neil Yorke‐Smith, Daniël Thalmann, Xingwei Wang, Hui Fang, Zhu Sun, Fajie Yuan, Yiheng Shu, Danning Zhang and Jie Zhang and has published in prestigious journals such as IEEE Access, Pattern Recognition and Information Sciences.

In The Last Decade

Guibing Guo

84 papers receiving 2.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings

2015 388 citations Guibing Guo, Jie Zhang et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Guibing Guo China	26	2.1k	1.4k	577	468	374	91	2.5k
Abraham Gutiérrez Spain	11	2.0k 1.0×	1.0k 0.7×	695 1.2×	417 0.9×	374 1.0×	41	2.5k
Zhumin Chen China	26	1.8k 0.9×	2.0k 1.5×	460 0.8×	273 0.6×	456 1.2×	97	2.9k
Yue Shi Netherlands	19	1.5k 0.7×	882 0.6×	570 1.0×	264 0.6×	398 1.1×	45	2.0k
Paolo Cremonesi Italy	23	2.1k 1.0×	1.1k 0.8×	871 1.5×	483 1.0×	608 1.6×	135	2.9k
Xiaoqiang Zhu China	8	1.8k 0.9×	1.3k 0.9×	823 1.4×	328 0.7×	453 1.2×	15	2.3k
Zhaochun Ren China	33	2.2k 1.1×	3.1k 2.2×	731 1.3×	240 0.5×	455 1.2×	147	3.9k
Kun Gai China	20	2.0k 1.0×	1.4k 1.0×	1.2k 2.1×	357 0.8×	538 1.4×	68	2.9k
Chang Zhou China	21	1.3k 0.6×	1.4k 1.0×	769 1.3×	282 0.6×	272 0.7×	53	2.2k
Ying Fan China	9	1.6k 0.8×	1.1k 0.8×	747 1.3×	303 0.6×	374 1.0×	24	2.1k

Countries citing papers authored by Guibing Guo

Since Specialization

Citations

This map shows the geographic impact of Guibing Guo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Guibing Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guibing Guo more than expected).

Fields of papers citing papers by Guibing Guo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guibing Guo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Guibing Guo. The network helps show where Guibing Guo may publish in the future.

Co-authorship network of co-authors of Guibing Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Guibing Guo. A scholar is included among the top collaborators of Guibing Guo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Guibing Guo. Guibing Guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Guo, Guibing, et al.. (2025). Symmetric Graph Contrastive Learning against Noisy Views for Recommendation. ACM Transactions on Information Systems. 43(3). 1–28.

2.

Shen, Li, et al.. (2024). Generalized Embedding Machines for Recommender Systems. arXiv (Cornell University). 21(3). 571–584. 1 indexed citations

3.

Liu, Yuting, et al.. (2024). Stealthy Attack on Large Language Model based Recommendation. 5839–5857. 1 indexed citations

4.

Guo, Guibing, et al.. (2024). Video and audio are images: A cross-modal mixer for original data on video–audio retrieval. Knowledge-Based Systems. 299. 112076–112076. 3 indexed citations

5.

Guo, Guibing, et al.. (2023). PESI: Personalized Explanation recommendation with Sentiment Inconsistency between ratings and reviews. Knowledge-Based Systems. 283. 111133–111133. 7 indexed citations

6.

Pan, Junwei, Ximei Wang, Haibin Yu, et al.. (2023). AdaTask: A Task-Aware Adaptive Learning Rate Approach to Multi-Task Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 37(9). 10745–10753. 30 indexed citations

7.

Yu, Yalin, et al.. (2023). Basket Representation Learning by Hypergraph Convolution on Repeated Items for Next-basket Recommendation. 2415–2422. 4 indexed citations

8.

Guo, Guibing, et al.. (2023). Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation. Proceedings of the AAAI Conference on Artificial Intelligence. 37(4). 4225–4232. 39 indexed citations

9.

Yuan, Fajie, et al.. (2019). Modeling the Past and Future Contexts for Session-based Recommendation.. arXiv (Cornell University). 1 indexed citations

10.

Sun, Shuai, Yuan Liu, & Guibing Guo. (2019). A Privacy-Preserving and Robust Reputation System Based on Blockchain. 634–639. 2 indexed citations

11.

Wei, Wei, Jiayi Liu, Xian-Ling Mao, et al.. (2019). Emotion-aware Chat Machine. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 1401–1410. 29 indexed citations

12.

Yuan, Fajie, Xin Xin, Xiangnan He, et al.. (2018). f BGD : Learning Embeddings From Positive Unlabeled Data with BGD.. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 198–207. 14 indexed citations

13.

Liu, Yun, et al.. (2018). BPRH: Bayesian personalized ranking for heterogeneous implicit feedback. Information Sciences. 453. 80–98. 69 indexed citations

14.

Guo, Guibing, et al.. (2017). Leveraging Multiactions to Improve Medical Personalized Ranking for Collaborative Filtering. Journal of Healthcare Engineering. 2017. 1–11. 1 indexed citations

15.

Guo, Guibing, Jie Zhang, Zhu Sun, & Neil Yorke‐Smith. (2015). Librec: a Java library for recommender systems. 1388. 94 indexed citations

16.

Guo, Guibing, Jie Zhang, Daniël Thalmann, & Neil Yorke‐Smith. (2014). ETAF: an extended trust antecedents framework for trust prediction. 540–547. 60 indexed citations

17.

Guo, Guibing, Jie Zhang, Daniël Thalmann, & Neil Yorke‐Smith. (2014). ETAF: An extended trust antecedents framework for trust prediction. 540–547. 82 indexed citations

18.

Guo, Guibing, Jie Zhang, Daniël Thalmann, & Neil Yorke‐Smith. (2014). Leveraging prior ratings for recommender systems in e-commerce. Electronic Commerce Research and Applications. 13(6). 440–455. 23 indexed citations

19.

Guo, Guibing. (2013). Improving the performance of recommender systems by alleviating the data sparsity and cold start problems. International Joint Conference on Artificial Intelligence. 3217–3218. 16 indexed citations

20.

Guo, Guibing, Jie Zhang, & Neil Yorke‐Smith. (2013). A novel Bayesian similarity measure for recommender systems. Scopus. 2619–2625. 140 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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